Optimization of FSRS with Anking Step Deck For Improvement of Rote Memorized Cards

Anki FSRS
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I’ve been using FSRS for Step 1 studying and ran into a recurring issue I’ve heard others mention too. FSRS is amazing for conceptual understanding, but fails with pure rote memorization.

FSRS assumes you’ve truly “learned” a card after a couple successful reviews. That’s perfect for big-picture, schema-based knowledge, but for rote Q&A Step 1-style facts (e.g. “drug X inhibits enzyme Y or X genetic marker is seen in Y disease”), you often get it right by recognition or chance early on. This creates “false stability” the illusion of a strong memory based on shallow recall. FSRS then overestimates your retention, sets long intervals, and the next time you see it you forget. I have a bunch of friends switching from FSRS back to SM-2 because they’re getting annoyed by this, but I don’t think that should be the case.

What I’d love suggestions on is how to assist with this issue. Globally making FSRS more aggressive isn’t what I’m looking for, since it works well for the big picture concepts. It’s the rote memorization topics that it is weak for. I’m thinking something like flagging all these cards as “Blue”, then hoping that could then auto assign a tag to it, something like “rotememorization.” Then having filtered decks in each subdeck of the Anking Step Deck for each organ system. I’ve attempted this but have had no luck in getting it to work properly since I have a limited understanding of how that system even works. I was hoping someone more inclined in anki’s user interface could be of assistance since I’d probably end up dedicating a bunch of time to trying to solve this and it’d be a mid ahh solution.

End goal is > Have Anking step deck split into my organ blocks per usual. For example, cardio/pulm or renal. Inside each of these classes is a filtered deck or something that can function similar that applies different FSRS settings to the cards flagged as blue / tagged. Making these cards somewhat easily interchangeable between tagged / not is paramount since there are a great deal of niche facts we need to memorize. I’d love to adjust cards as we go. See it, notice it’s not in the big pic schema, flag. Move on. The tagged cards are then more aggressively scheduled with either a decreased easy interval modifier or something like that (idrk how that works). Please help i love you anki squad.

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Hi, interesting post, I have questions

  • This note is divided in separate cards? Can you share screenshot from it? I would like to check if you use cloze and how.
  • can you share statistics from deck where FSRS did not work?
  • How many configs do you use so far? One global? Per note type? Per deck?
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The above note was simply an example. Actual cards are typical cloze, similar to below.

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Stats will probably be skewed from my use but I’ll ask my friend to send me his who was having more of the issue with it. I’ve adjusted settings / suspended leechier cards to try and make it less of a problem. Which stats are you specifically looking to see? It won’t let me upload the full PDF of it onto the forums.

I use a different config for each deck, each organ system is separated into its own deck. Note types are pretty consistent just standard cloze, utilizing the AnKing Step Deck with a few of my own cards thrown in, that are also Cloze.

Biggest issue is getting a card right could be due to A. Foundational knowledge / conceptual integration or B. rote memorizing the card or question/answer. If it’s A. the FSRS settings work beautifully. If it’s B the card feels incredibly unstable. Problem is with the Step Deck we need to learn alot of cards through rote memorization. Conceptual mastery of all of it isn’t feasible given the breadth of information to learn. So it’d be nice to selectively schedule specific rotely memorized cards in one organ system more aggressively, while maintaining normal scheduling for the foundational knowledge.

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I would like to check your / your collogue true retention, how many cards and what type of cards you do; how long have you been learning